In an agent-first enterprise, AI systems drive processes while humans set goals, define policy constraints and handle exceptions.
“You need to shift the operating model to humans as governors and agents,” says Scott Rogers, global chief architect and USCTO of Deloitte’s Microsoft technology practice.
Agent – ​​First essential
With technology budgets for AI expected to increase by more than 70% in the next two years, AI agents, powered by generative AI, are poised to fundamentally transform organizations and achieve results beyond traditional automation. These initiatives have the potential to generate significant performance gains by shifting people to higher value work.
AI is advancing so rapidly that a static approach to task automation will likely only produce incremental benefits. Because legacy processes are not designed for autonomous systems, AI agents require machine-readable process definitions, clear policy constraints, and structured data flows.
To further complicate matters, many organizations do not understand the full economic drivers of their business, such as cost to serve and cost per transaction. As a result, they have difficulty prioritizing agents who can generate maximum value and instead focus on flashy pilots. To achieve structural change, executives must think differently.
Instead, companies must produce results faster than competitors. “The real risk isn’t that AI won’t work — it’s that competitors will redesign their operating models while you’re still piloting agents and copilots,” says Rodgers. “Nonlinear benefits are realized when companies create agent-based workflows with human governance and adaptive orchestration.”
Routine and repetitive tasks are increasingly automated, freeing employees to focus on high-value, creative, and strategic work. This shift improves operational efficiency, fosters stronger collaboration, and creates faster decision-making—helping organizations modernize the workplace without sacrificing enterprise security.
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